Implantable medical devices (IMDs) are devices designed to be implanted into a patient. Some examples of these devices include cardiac function management (CFM) devices. CFMs include implantable pacemakers, implantable cardioverter defibrillators (ICDs), and devices that include a combination of pacing and defibrillation including cardiac resynchronization therapy. The devices are typically used to treat patients using electrical therapy and to aid a physician or caregiver in patient diagnosis through internal monitoring of a patient's condition. The devices may include electrical leads in communication with sense amplifiers to monitor electrical heart activity within a patient, and often include sensors to monitor other internal patient parameters. Other examples of implantable medical devices include implantable insulin pumps or devices implanted to administer drugs to a patient.
Additionally, some IMDs detect events by monitoring electrical heart activity signals. In CFM devices, these events include heart chamber expansions or contractions. By monitoring cardiac signals indicative of expansions or contractions, IMDs are able to detect abnormally rapid heart rate, or tachyarrhythmia. Some tachyarrhythmia is treated by delivering high-energy electrical shock therapy with the IMD.
Patients that use IMDs may be adversely affected by misinterpretations of signals sensed by the IMD sensing circuits. If an IMD incorrectly interprets a sensed signal as indicating tachyarrhythmia, the IMDs may inappropriately deliver shock therapy, causing patient discomfort. Atrial fibrillation (AF) is a form of tachyarrhythmia not typically treated with shock therapy. However, AF may be incorrectly interpreted as ventricular tachycardia (VT), which is often treated with shock therapy, causing incorrect identification of AF a leading cause of inappropriate therapy delivery. The rate of inappropriate deliveries has not been shown to be significantly different between single chamber CFM devices and multi-chamber CFM devices using existing AF detection algorithms. Thus, there is a need for improved sensing of events related to device recognition and classification of tachyarrhythmia.